Comorbidity of mental and medical illness is a major problem compromising the health of a significant number of Americans. Comorbid medical and mental illnesses are far more prevalent than previously thought and have a negative impact greater than the sum of either illness alone. Failure to appreciate the presence of comorbidity when researching the predictors or consequences of either illness alone can significantly compromise not only diagnosis and treatment of the affected patient but the impact of both illnesses on the health of the public overall. In the proposed study we capitalize on the availability of a long term, carefully selected longitudinal community cohort of 2500 white and African American (36 percent) men (25 percent) and women in mid to later life (45 year and older) who are participating in an ongoing study on the epidemiology of osteoarthritis. Drawing on two previous waves of data collected from this cohort in 1995-1999 and 1999-2002, we propose re-interviewing these 2500 individuals at two additional points of time over the next 5 years (between 2001-2005). Our proposed interviews will include the administration of a well established standardized psychiatric diagnostic interview which will allow us to identify people in this community who do and do not meet the diagnostic criteria for depressive and/or anxiety disorders. We also will explore several psychometric issues and controversies related to the measurement of psychological and psychiatric distress. Finally, we use a theoretically-informed conceptual framework to identify risk-producing and protective factors for psychiatric comorbidity and test hypotheses about their mechanisms of action and consequences for health and well being. Data analysis approaches will include multiple logistic regression - dichotomous or polytomous, as appropriate, logistic regression based on generalized estimating equations (GEE) and models based on Item Response Theory.